37 results about "Drugs types" patented technology

The invention discloses an intelligent dosing system and method based on machine learning, and the method comprises the steps: S1, collecting fluidized bed operation parameters and water quality characteristic data in real time, including water flow dynamic parameters, water quality index parameters and particle morphology parameters, and constructing a time sequence characteristic database; s2, constructing a dynamic dosing model based on the fluidized bed by using data in the time sequence characteristic database, and performing joint prediction on the medicament type, the dosing amount and the operation parameters; s3, according to a prediction result output by the model, controlling the agent dosage, the agent concentration, the water flow speed and the aeration intensity; and S4, monitoring the fluidized bed and dosing control parameters in real time, and dynamically correcting the fluidized bed parameters in combination with the effluent turbidity of the fluidized bed and the particle sedimentation efficiency, so as to solve the problems that the sewage treatment effect in the prior art is poor, and medicament waste, substandard treatment and secondary environmental pollution are possibly caused.

The invention discloses a method and device for taking medicine from a medicine storage box, electronic equipment and a storage medium, and the method comprises the steps that medicine taking information is received, and the medicine taking information comprises a plurality of pre-taken medicine types and the pre-taken number corresponding to each pre-taken medicine type; and in each grabbing process, some medicines are grabbed as much as possible. According to the method, the medicine grabbing efficiency can be greatly improved.

The embodiment of the invention provides a medicine evaluation method and related equipment, and belongs to the technical field of information processing. The method comprises the following steps: acquiring medicine input information corresponding to a first medicine; the first medicine is any medicine, and the medicine input information comprises medicine type data; generating a corresponding medicine evaluation template according to medicine type data in the medicine input information; collecting expert evaluation information corresponding to the first drug through the drug evaluation template; the expert evaluation information comprises text data and score data; and performing text analysis on the text data corresponding to the first drug through the drug evaluation model to generate a model evaluation score, and integrating the model evaluation score and the score data to obtain a target evaluation result corresponding to the first drug. According to the embodiment of the invention, the consistency and objectivity of the drug evaluation result can be remarkably improved, so that more comprehensive and intelligent decision support is provided for drug selection of medical institutions.

The invention relates to the technical field of medical evaluation, in particular to a basic drug use tendency evaluation method and device, a medium and a product. The method comprises the following steps: acquiring a disease type, a patient specific attribute and medication information of a target patient; according to a standard evidence-based intensity database, determining intermediate evidence-based intensity of each drug type in the medication information in disease types, patient specific attributes and medication schemes; obtaining attribute information of a target hospital seeing a doctor by the target patient, and adjusting the intermediate evidence-based intensity based on the attribute information to obtain the actual evidence-based intensity of the target patient; determining the average standard evidence-based intensity of each base drug type corresponding to the disease type; and calculating a difference value between the actual evidence-based intensity and the average standard evidence-based intensity as a base drug use tendency degree, and generating a drug use rationality evaluation result for the target patient according to the base drug use tendency degree. According to the invention, multi-dimensional evaluation can be carried out on the drug use rationality of the patient, and the accuracy of the evaluation result is improved.

An analysis method for detecting multiple residual solvents during the preparation process of a drug. In the method, a gas chromatographic method is utilized to simultaneously detect 21 organic solvents, i.e. methanol, tetrahydrofuran, ethanol, cyclohexane, diethyl ether, isopropyl acetate, acetone, n-heptane, isopropanol, n-butyl alcohol, acetonitrile, dioxane, dichloromethane, pyridine, tert-butyl alcohol, toluene, tert-butyl methyl ether, N,N-dimethylformamide, n-hexane, dimethyl sulfoxide and ethyl acetate. The method is free from influence of drug types, can be applied to the content detection of multiple residual solvents in drugs, has simple operation and a wide usable range, and saves on the time and cost for drug detection.

The present invention provides a method and device for arranging a medicine storehouse, the method comprising the following steps: obtaining multiple drug types stored in the medicine storehouse and the total quantity corresponding to each drug type; when the total quantity corresponding to any target drug type is less than a first preset threshold, obtaining a plurality of medicine baskets to be merged whose drug type is the target drug type and whose drug quantity is less than a second preset threshold, and performing the following first processing on each medicine basket to be merged: the number of drugs in the medicine basket to be merged is Num1, obtaining a first target medicine basket whose drug type is the target drug type, and the number of drugs in the first target medicine basket + Num1 ≤ Num2, and conveying all drugs in the medicine basket to be merged to the first target medicine basket. Thus, some empty medicine baskets can be freed up.

The present invention discloses a method for efficiently determining 14 kinds of psychotropic drugs, comprising the following steps: obtaining a sample to be tested; detecting the sample to be tested by high performance liquid chromatography tandem mass spectrometry, and performing quantitative analysis by an external standard method. The present invention simultaneously determines the concentrations of 14 common psychotropic drugs, which can not only avoid the problem of a single drug type, low throughput, affecting the efficiency of detection, and being unfavorable for carrying out more detection projects; but also avoids the phenomenon of detecting too many drug types, high costs, and waste of resources.

This invention relates to the field of medical data and discloses a method for real-time monitoring of the efficacy of traditional Chinese medicine, Mongolian medicine, and Western medicine based on biosensor technology. This method enables real-time monitoring of drug efficacy and personalized medication guidance. The process includes collecting real-time multimodal biosignals from the user's body surface or minimally invasive body fluid samples to obtain raw sensor signals and acquire sensor array output; extracting real-time pharmacokinetic characteristic signals based on a preset pharmacokinetic model and mapping them to efficacy assessment parameters according to drug type; comparing the efficacy assessment parameters with a preset safe and effective concentration range to generate real-time medication status indicators and dosage adjustment prompts. This invention designs quantitative assessment methods for different types of drugs, enabling real-time comparison to generate efficacy status codes and dosage adjustment suggestions. It comprehensively generates a medication guidance report and transmits it in real-time to the user or clinical monitoring end, allowing for immediate adjustment of the medication regimen and ensuring safe and effective medication.

The present application relates to the technical field of artificial intelligence, and particularly relates to an individualized medication prediction method based on artificial intelligence, comprising: acquiring a plurality of standard historical medical data sets; acquiring metabolic capacity scores and drug metabolism rates corresponding to all data groups; training to obtain relationship models corresponding to all standard historical medical data sets; acquiring liver metabolism parameters, gene expression parameters and each drug name in a treatment scheme of a patient to obtain a drug metabolism rate; and determining a corresponding prediction drug amount determination method according to whether the drug types in the treatment scheme have a competitive relationship. The present application integrates drug metabolism enzyme-related gene expression and liver metabolism function, simultaneously incorporates drug absorption competition and metabolism enzyme competition when drugs are used in combination, corrects the final output prediction drug amount when drugs are used in combination, so that the model is more suitable for the actual drug use scene, and the accuracy of the prediction result is increased.

The application discloses an electrically-controlled drug-loaded hot compress patch, a control circuit and a control method. The control circuit comprises a drug-loaded hot compress patch and a controller. The drug-loaded hot compress patch and the controller are connected. The drug-loaded hot compress patch comprises a drug-loaded layer, a heating layer and a fixing belt. The heating layer is arranged on the drug-loaded layer. The fixing belt is arranged on the heating layer. The drug type of the drug-loaded layer is selected based on user demand. The drug-loaded layer and the heating layer are detachably connected. A plurality of electric heating patches are arranged on the heating layer. The heating layer is used for heating the drug-loaded layer. The fixing belt is used for fixing the drug-loaded layer to the human skin. The controller controls the electric heating patches in the heating layer based on the effective release temperature of the drug on the drug-loaded layer.

The invention discloses a composition, a method and a system for predicting the applicability of antipsychotic drugs. The invention develops a composition, a detection kit, a model construction method and a system for predicting the applicability of antipsychotic drugs on the basis of selected SNP site information. Particularly, a gene marker combination related to the curative effects of the antipsychotic drugs olanzapine, risperidone, aripiprazole and quetiapine is found by adopting a large-sample high-throughput whole-genome association analysis technology, and a corresponding mathematical model for predicting the curative effects is constructed; the model can be used for predicting the PANSS subtraction rate after the schizophrenia is treated by medication based on DNA polymorphic sites and clinical basic information of a medication user in a high, medium and low classification manner, and assists in guiding the selection of the types of the medication, so that personalized treatment of the schizophrenia patient is realized.

The invention belongs to the field of analytical chemistry, and particularly relates to an analysis method for detecting multiple residual solvents in a medicine preparation process. According to the method, 21 organic solvents including methanol, tetrahydrofuran, ethanol, cyclohexane, diethyl ether, isopropyl acetate, acetone, n-heptane, isopropanol, n-butyl alcohol, acetonitrile, dioxane, dichloromethane, pyridine, tert-butyl alcohol, toluene, tert-butyl methyl ether, N, N-dimethylformamide, n-hexane, dimethyl sulfoxide and ethyl acetate are simultaneously detected by adopting a gas chromatographic method. The method is not influenced by drug types, can be applied to content detection of various drug residual solvents, is simple to operate and wide in application, and saves drug detection time and detection cost.

This invention discloses an automated dispensing device for injectable drugs, belonging to the field of medical device automation technology. The device includes a pluggable drug storage compartment and a dispensing base. A bottle guide ramp and a conical multi-position screw feeder work together to achieve self-alignment and precise bottle pickup. A dynamic locking mechanism automatically locks / unlocks the transmission system during insertion and removal to ensure safety. An RFID system verifies the drug type to prevent errors. Electromechanical dual overload protection prevents damage to the equipment and bottles. Photoelectric closed-loop counting and intelligent empty detection ensure accurate and continuous dispensing. This invention offers accurate and reliable dispensing, safe operation, and a high degree of intelligence.

The invention discloses a drug delivery carrier material, a drug delivery coating and a preparation method thereof, and belongs to the technical field of biological materials. The preparation method of the drug delivery coating comprises the following steps: reacting polypeptide containing hydrophobic amino acid with acidic protein in a solution system in which the pH value is 3-7, the temperature is 20-50 DEG C and an oxidizing agent exists, and mixing the prepared coating with a drug solution to realize drug filling, and then mixing with a phosphate solution to induce the micro-nano pore structure in the coating to be closed. The isoelectric points of the polypeptide and the acidic protein are both less than 7, and the difference value of the isoelectric points is less than or equal to 2.5; the acidic protein is negatively charged under the condition that the pH is greater than or equal to 7. According to the method, the contradiction that high loading and low burst release of an existing carrier are difficult to achieve at the same time is effectively solved, the coating is mild in drug loading condition, effective loading and activity retention of various active biomolecules can be achieved, the coating can also adapt to various drug types through modular design, and a brand new mode is provided for constructing a next-generation intelligent drug delivery system.

The invention provides a GIST targeted drug type selection prediction method and system based on artificial intelligence, and the method comprises the steps: obtaining a digital pathological image of a tissue pathological section of a target object, and inputting the digital pathological image into a GIST targeted drug type selection prediction model, the generation method of the GIST targeted drug type selection prediction model comprises the steps that the digital pathological image of a tissue pathological section used for model training is obtained, the digital pathological image is cut into a plurality of block images, corresponding position information is obtained, and a target drug type prediction result corresponding to the digital pathological image is obtained. Associating the block images with pseudo labels, inputting the block images into a feature extraction network, learning and training the feature extraction network by using weak supervision features to obtain a feature extractor, and extracting features of all the block images by the feature extractor; and inputting the features and the position information into a neural network model for training to obtain a GIST targeted drug type selection prediction model.

The present invention discloses an artificial intelligence-based drug vigilance system access system and method, a drug query module, the drug query module is used to query the drug type to be accessed; the patient information acquisition module is used to obtain various related information of the drug trial patients of the drug type to be accessed in the drug query module; the verification and checking module is used to perform logical verification on the various related information of the drug trial patients of the drug type to be accessed obtained in the patient information acquisition module, judge whether there is suspicious information in the related information, and perform manual verification on the suspicious information; the drug vigilance report generation module is used to summarize the various related information of the drug trial patients of the drug type to be accessed that have passed the verification and checking in the verification and checking module, obtain the drug vigilance report corresponding to each drug trial patient, and judge the priority of the drug vigilance report according to the content of the drug vigilance report.

The invention provides a nanoparticle composition as well as a preparation method and application thereof. The nano-particle composition comprises the charged nano-particles and the loaded drug, and the drug loading efficiency is remarkably improved by treating a mixed solution of the nano-particles and the drug through low-temperature plasma jet. According to the method, the electrical property of the nano-particles is changed by utilizing low-temperature plasma, so that the adsorption capacity of the nano-particles on charged drugs is enhanced, and the method is suitable for various drug types such as small molecule drugs, gene drugs and proteins. Experimental results show that the drug loading capacity is remarkably improved in multiple drug loading systems, the method has the advantages of being easy to operate, non-toxic, low in cost and the like, and the method is suitable for industrial production and promotes application of drug delivery carriers in the medical field.

This specification discloses a method, device, and medium for drug supervision based on blockchain. The method includes: dividing a drug storage cabinet into multiple storage areas and collecting current environmental information and current drug information from each storage area; the current environmental information includes current temperature, current humidity, and current light conditions; determining whether the drug is stored in a pre-defined storage area based on the correspondence between drug type identifiers and multiple storage areas; if the drug is placed in a pre-defined storage area, storing the current environmental information corresponding to the storage area on the blockchain for monitoring the current environmental information within the storage area; issuing an early warning message; and determining the environmental control object to be adjusted based on the environmental information to be adjusted and the target storage area to be adjusted in the early warning message, and sending environmental control instructions to the environmental control object to be adjusted to achieve drug supervision.

The present invention provides a method and system for automatically determining the dosage of personalized medication adjustment. The present invention calculates the initial medication regimen based on the patient's physiological data and medication types, using the weighted results of a one-compartment model and a two-compartment model. At the same time, when the patient's initial medication regimen is ineffective or has adverse reactions, the patient's medication regimen is adjusted. Compared with the prior art, the present invention can not only accurately predict and adjust the medication dosage, but also provide adjustment suggestions in real time through a feedback mechanism to ensure the safety and efficacy of personalized medication.

The present invention provides a drug identification device, a drug identification method, and a program capable of, even when there is a drug with a drug surface the same as or similar to an identification target surface of an identification target drug in drug identification using single-sided imaging and single-sided image input, notifying a user of existence of the drug with the same or similar drug surface and enabling the user to determine a correct drug as the identification target drug. The present invention acquires a plurality of drug surface candidates which are candidates for correct answers of an identification target surface of an identification target drug on the basis of an identification target image of the identification target surface, and displays, for a drug type candidate with a drug surface candidate as a quasi-identifiable surface, a first master image of the drug surface candidate and a second master image of the opposite-side surface of the drug surface candidate, and displays an alert on the first master image or at a position associated with the first master image.

The invention discloses a medicine filling dose automatic identification method and system, and relates to the technical field of production automation, a medicine main database and a main learning model are established, and the main learning model differentiates a corresponding derived learning model according to a medicine type; generating a lightweight learning model for each production batch of each type of medicine based on the derived learning model of each type of medicine, performing adaptive compensation adjustment on parameters of each level of the lightweight learning model based on difference information of the production batches, and fusing each level by outputting a corresponding dynamic fusion coefficient; and monitoring the operation process of each lightweight learning model based on a preset task trigger event, carrying out parameter retraining on the lightweight learning model by sharing the difference characteristic parameters, and carrying out canned dose real-time monitoring identification by using the retrained lightweight learning model. Automatic high-precision monitoring and intelligent optimization in the medicine production process are achieved, and the production efficiency and the product quality are improved.

The present invention provides a method for analyzing the forming and stability of a shaped charge jet, which first performs a jet forming analysis on a shaped charge jet formed by the detonation wave generated by the detonation of explosives crushing a charge liner, so as to establish the relationship between the liner structural parameters and the jet diameter, temperature and strain rate; then performs a jet stability analysis on the shaped charge jet to determine the jet instability criterion; and finally obtains the jet break time. The present invention establishes the relationship between the shaped charge liner structural parameters and the jet diameter, temperature and strain rate, proposes a jet stability criterion and a jet break time evaluation method that comprehensively considers strain hardening, strain rate effect, thermal effect and necking effect, constructs an analysis method for the effect of liner structural parameters on jet stability, and effectively analyzes jet stability.

The invention belongs to the technical field of drug detection, and provides a drug type identification method and system based on a sensor array. The method comprises the following steps: acquiring a response data time sequence of at least three sensors in a sensor array; extracting a steady-state feature and more than one dynamic feature corresponding to the sensor based on the response data time sequence of the sensor, the steady-state feature being a ratio of a response data average value in a tail data segment to a response data average value in an initial data segment in the response data time sequence; the more than one dynamic feature at least comprises a response data accumulated value of a predefined response region in the response data time sequence; and based on the steady-state features corresponding to the at least three sensors and the more than one dynamic feature, utilizing a classification model to obtain a drug type identification result of the to-be-detected article. The invention also provides a drug type identification system. The method is extremely low in cost, easy to operate, small in calculation amount and capable of rapidly and accurately achieving identification of various drugs.

According to the poison condition monitoring method and system, the message data in the communication software is acquired, the message data is mined and analyzed, the poison-related users in the communication software are determined and the poison-related labels are marked, and the poison-related users are automatically analyzed and the poison-related labels are marked, so that the difficulty and the consumed time of manual analysis are reduced, and the efficiency is improved; according to the method, the drug-related information of the corresponding drug-related user is extracted from the message data according to the drug-related label, a figure portrait is generated, the drug-related information comprises at least one of the activity area, the contact information, the drug type and the transaction information, and then the figure portrait is displayed, so that monitoring personnel can quickly and directly obtain the figure portrait of the drug-related person, and the monitoring efficiency is improved. Effective reference is provided for monitoring personnel, and the monitoring efficiency and effect can be improved.

The present application discloses a patient labeling method, device, equipment and storage medium based on hierarchical calculation, which relates to the field of smart medical technology. For target patients who do not hit the high-risk diagnostic label, high-risk drug label and drug type threshold of the target disease in the target disease, the historical number of medical visits and historical medical record labels are analyzed, and hierarchical identification is used to identify in multiple dimensions to ensure comprehensive identification of risks and improve labeling accuracy. The method includes: obtaining high-risk diagnostic labels, high-risk drug labels and drug type thresholds; determining the target patient among the patients to be labeled for the target disease; counting the historical number of medical visits of the target patient in the historical time period; when the historical number of medical visits is greater than or equal to the medical number threshold, obtaining the historical medical records of the target patient, using a natural language processing algorithm to identify the historical medical records, determining the project indicators of the target patient, and marking the target patient using the risk label corresponding to the project indicator.

The present invention provides a method for evaluating the neurotoxicity of environmental residues of quinolone antibiotics based on network toxicology. The present invention collects the types of quinolone drugs remaining in the environment and their drug targets, and collects neuropsychiatric diseases and their disease genes; establishes a drug target network, a neuropsychiatric disease module, and an overlapping network of drug target-disease modules, calculates network parameters to obtain key genes, uses the DAVID database to perform enrichment analysis on the key genes, and then performs network ranking analysis. Compared with traditional methods, the network toxicology of the present invention using big data high-throughput integration analysis technology has a wide coverage range of research objects, considers the toxicity of drugs from the perspectives of drug targets and disease genes, and provides a new idea for evaluating the risk size of adverse reactions of compounds.

A control system (1) for an infusion pump (2) comprises: a processor assembly (10); and a memory (11) storing instructions (12) that, when executed by the processor assembly (10), cause the processor assembly (10) to perform the steps of: receiving a dose of medicament and a type of medicament; reading a drug data structure (130) corresponding to the received drug type from a drug library (13), the drug library (13) adapted to store a plurality of drug data structures (130), each drug data structure (130) comprising a drug type entry (131) indicative of a drug type and a dose evolution entry (132) adapted to indicate whether a dose rate or a flow rate is to be kept constant over time; and determining an updated drug dose for the received drug type based on the dose evolution entry (132).

The utility model discloses a detector capable of detecting various drugs. The detector comprises a containing module and a detection module, wherein the detection module comprises a circular detection table, and the upper side of the circular detection table is fixedly connected with a circular boss. When the device is used, a urine sample of a suspected person is collected into the urine containing cylinder, the urine containing cylinder is placed into the cylinder, the clamping blocks are embedded into the clamping grooves, the urine containing cylinder is fixed, at the moment, the group of round holes correspond to the inclined grooves, the sleeve is moved upwards, the group of round holes are exposed, and the urine containing cylinder is fixed. Urine in the urine containing cylinder enters the inclined groove through the round hole and flows onto the detection test paper in the test paper containing groove, the urine reacts with the detection test paper, the detection test paper in the corresponding reaction is observed, name labels of drug types in the corresponding label containing groove are observed, and then a common drug rapid detection result can be obtained.

Anti-Aβ drug screening targets and a drug screening method. The screening method uses different Aβ aggregates prepared by simulating the in vivo environment and conditions as targets, to more accurately and effectively screen anti-Aβ candidate drugs; the Aβ targets involved in the screening method are aggregated and incubated under conditions approaching different in vivo microenvironments, and do not require labeling or modification; in addition, the screened drug molecules do not require any modification or labeling, and are not limited to any specific drug class, being widely applicable to different drug types, such as antibodies, peptides and small molecules, truly reflecting the interactions between targets and these drug molecules, greatly reducing the likelihood of problems such as false positives, false negatives or incorrect binding modes.

A control system (1) for an infusion pump (2) comprises: a processor assembly (10); and memory (11), the memory (11) storing instructions (12) that, when executed by the processor assembly (10), cause the processor assembly (10) to perform the following steps: receive a drug dosage and a drug type; read a drug data structure (130) corresponding to the received drug type from a drug library (13), the drug library (13) being adapted to store a plurality of drug data structures (130), each drug data structure (130) comprising a drug type entry (131) indicating a drug type and a dosage evolution entry (132) adapted to indicate whether a dose rate or a flow rate is to be maintained constant over time; and determine an updated drug dosage for the received drug type based on the dosage evolution entry (132).